class_docstr: Cropping layer for 1D input (e.g. temporal sequence).
  The input of this layer should be 3D.
  
  When you use this layer as the first layer of a model, you need to provide the argument
  input_shape (a shape tuple, does not include the batch dimension).
  
  # Arguments
  cropping: Int tuple of length 2. How many units should be trimmed off at the beginning and
            end of the cropping dimension. Default is (1, 1).
  input_shape: A shape tuple, not including batch.
  name: String to set the name of the layer.
        If not specified, its name will by default to be a generated string.
  
  >>> cropping1d = Cropping1D(cropping=(1, 2), input_shape=(8, 8))
  creating: createZooKeras2Cropping1D
code: def __init__(self, cropping=(1, 1), input_shape=None, **kwargs):
      super(Cropping1D, self).__init__(
          None,
          cropping,
          list(input_shape) if input_shape else None,
          **kwargs,
      )
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/keras2/layers/convolutional.py
imports: import sys
  from zoo.pipeline.api.keras2.base import ZooKeras2Layer
label_desc: Use image node_id 1 to create a new Cropping1D object from inherited base classes: ZooKeras2Layer with example: obj = Cropping1D(cropping, input_shape)